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Objective
The goal of the this tutorial is to deploy an Apache HTTP Server using helm chart on GKE Cluster through FlexDeploy Helm pluginHelm Chart on a Google Kubernetes Engine (GKE) cluster through FlexDeploy using the Helm Plugin. For this tutorial, we shall will be doing setting up an automated deployment of the an Apache HTTP Server , using the helm chart Helm Chart which is present at in this chart repository (https://charts.bitnami.com/bitnami) . The steps will include:
configuration of the Configuring properties e.g. config file path, Cloud cloud account, and CLI path .
deploying Deploying the Apache HTTP Server to a GKE Cluster cluster
verifying Verifying the application is successfully created on the GKE cluster.
We will walk through each of the FlexDeploy features that will be created/configured to accomplish this goal and have the Apache HTTP Server deployed on the GKE Cluster cluster in a very short amount of time.
Checklist
Checklist | Description |
GCP Project Id | Project Id to connect to desired GCP project. |
GCP Key File | The GCP Key File to connect GKE cluster. |
GCP CLI installation | GCP CLI needs to be installed where the plugin operation |
will run (generally the FlexDeploy server) | |
GCP CLI in class path | GCP CLI should be added to class path on the FlexDeploy Server. Else the path can also be set under FlexDeploy environment level property |
GKE Setup | GKE cluster should be created in GCP and a kubeconfig file should be present with the context of the cluster. |
Configure Cloud
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Account
To connect with GKE cluster, we required to configure Cloud account, with credentials details. Configure GCP Cloud Account under Integration. FlexDeploy will connect to the GKE cluster and deploy the Apache HTTP Server.
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It should have a Project Id and Key File configured in it. The user must have relevant access to do the deployment on GKE cluster.
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Key File is a password field and hence needs to be kept hidden. To update the same it, click on the pencil icon as shown below
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2. Update the entire Key File value under Secret Text. This is to make sure no one else can retrieve the password
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After configuration configuring, we can use the Cloud Accountcloud account.
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Prerequisites
Configure
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Service Account
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To access the GKE cluster, we need to create a service account.
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The entire content of the key file we have to configured in GCP Cloud account as secret text.
Configure kubeconfig
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File
A Kubeconfig is a YAML file with the details to connect to Kubernetes Cluster cluster using certificate/secret tokens to authenticate the cluster. This is essential for Helm Plugin to connect to target GKE cluster.
CLI
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Installation
GCP CLI should be installed in the m/c where the plugin is to be executed. Preferably add GCP CLI path in m/c classpath. Please ref. https://cloud.google.com/sdk/docs/install for more information about installation.
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Deploy Workflow
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Navigate to
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Workflows and create a
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The Workflow Group and Subgroup define the folder hierarchy. Once both workflows are created it should look like the below. No constraint on workflow or folder naming convention.
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The steps of the workflow execution can be configured through the Workflow Definition section.
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Below given workflow using the 
button as highlighted below.
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Below is a sample deploy workflow to deploy the application on the a GKE cluster.
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Step-i: deploy the application
This step will deploy the Apache HTTP Server on the GKE cluster, using the helm chart Helm Chart which is present at chart repository (https://charts.bitnami.com/bitnami) . Context must be provided to apply changes. The context should be present inside kubeconfig file.
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In above configuration using following Inputsinputs, for all input and their description please ref. refer to the plugin documentation: deploy (Helm)
Input Name | Input Value | Description |
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Chart Name | apache | Name of a chart to be installed. (Reference/Package/Directory/URL). If empty takes the chart name from the project configuration. |
K8s Context | k8s-test-cluster | K8s Context where the chart will be installed |
Release Name | test- |
Helm-new | Release name. If empty takes the chart name from the project configuration. If unspecified, it will autogenerate one for you | |
Repository Name | Name of a chart repository | |
Config file | /home/oracle/.kube/azure/config | K8s config file |
Project configuration
Navigate to the Project tab and create a Project with a logical name(Helm in this case)
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Configure the Deploy workflow that has been created in previous steps as shown below.
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Target Properties
Select Topology from the menu and then select Targets from menu. Select the target group and environment, provide the properties detail, according to the description.
Properties | Mandatory field | Description |
Cloud Account | Optional | Select the Cloud Account to connect cluster. |
CLI Path | Optional | Directory where Cloud CLI is installed. |
Kubeconfig File Path | Optional | Absolute path of kubeconfig file |
Below given are the environment-specific values which need to be updated.
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Cloud Account
The GCP Cloud account needs to be set here from the drop-down. It will show all Cloud Accounts configured under Topology, which we have already mentioned earlier.
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Kubeconfig file path
Absolute path of config file can be set as environment property, if path is not set then by default plugin look for config file in user directory.
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CLI path
GCP CLI path can be set as environment property, if it’s not set then by default plugin use classpath.
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Override properties at Project level
Let assume a scenario, where we want to change Cloud account for any specific project. Apart from setting at environment level, it can also be set at project properties by using Override Property. Please check below mentioned steps.
Navigate to the Project Configuration tab as shown above.
Next, select the PROPERTIES option from the left-hand pane.
Click on the OVERRIDE option.
Select the Cloud Account option from Property.
Select the Environment from the drop down list.
Select the Target Group from the drop down list.
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Build Execution
For detailed steps on how to initiate deploy operation using Helm plugin, please refer to Deploy through FlexDeploy using Helm plugin
Post deployment
Post deployment success from plugin it can take a little while for the deployment and running.
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